This course aims to teach learners how to build recommendation systems, work with natural language processing (NLP) techniques, utilize neural structured learning, delve into machine learning concepts, and explore TensorFlow functionalities such as TensorFlow Extended and TensorFlow Lite. The course covers topics like content-based filtering, collaborative filtering, sentiment analysis, neural networks, convolutional neural networks, and distributed processing. The teaching method includes coding exercises, tutorials, and practical demonstrations. This course is intended for individuals interested in expanding their knowledge of TensorFlow, machine learning, NLP, and recommendation systems.
Overview
Syllabus
Recommendation systems overview (Building recommendation systems with TensorFlow).
Content-based filtering & collaborative filtering (Building recommendation systems with TensorFlow).
Intro to TensorFlow Recommenders (Building recommendation systems with TensorFlow).
Building a ranking model with TF Recommenders (Building recommendation systems with TensorFlow).
Leveraging context features and multitask learning (Building recommendation systems with TensorFlow).
Deep & Cross Network (Building recommendation systems with TensorFlow).
Efficient serving with ScaNN for retrieval (Building recommendation systems with TensorFlow).
Natural Language Processing - Tokenization (NLP Zero to Hero - Part 1).
Sequencing - Turning sentences into data (NLP Zero to Hero - Part 2).
Training a model to recognize sentiment in text (NLP Zero to Hero - Part 3).
ML with Recurrent Neural Networks (NLP Zero to Hero - Part 4).
Long Short-Term Memory for NLP (NLP Zero to Hero - Part 5).
Training an AI to create poetry (NLP Zero to Hero - Part 6).
Neural Structured Learning - Part 1: Framework overview.
Neural Structured Learning - Part 2: Training with natural graphs.
Neural Structured Learning - Part 3: Training with synthesized graphs.
Neural Structured Learning - Part 4: Adversarial learning for image classification.
Announcing TensorFlow 2.0 (Coding TensorFlow).
Build an image classifier (ML Zero to Hero - Part 4).
Introducing convolutional neural networks (ML Zero to Hero - Part 3).
Basic Computer Vision with ML (ML Zero to Hero - Part 2).
Intro to Machine Learning (ML Zero to Hero - Part 1).
Distributed Processing and Components (TensorFlow Extended).
Why do I need metadata? (TensorFlow Extended).
How do TFX pipelines work? (TensorFlow Extended).
What exactly is this TFX thing? (TensorFlow Extended).
Get started with using TensorFlow to solve for regression problems (Coding TensorFlow).
Upgrade your existing code for TensorFlow 2.0 (Coding TensorFlow).
How to take advantage of GPUs and TPUs for your ML project (Coding TensorFlow).
Build a deep neural network in 4 mins with TensorFlow in Colab.
Getting Started with TensorFlow in Google Colaboratory (Coding TensorFlow).
Get started with Google Colaboratory (Coding TensorFlow).
TensorFlow Lite, Experimental GPU Delegate (Coding TensorFlow).
TensorFlow high-level APIs: Part 3 - Building and refining your models.
TensorFlow high-level APIs: Part 2 - going deep on data and features.
TensorFlow high-level APIs: Part 1 - loading data.
Saving and Loading Models (Coding TensorFlow).
Solve your model’s overfitting and underfitting problems - Pt.2 (Coding TensorFlow).
Solve your model’s overfitting and underfitting problems - Pt.1 (Coding TensorFlow).
Designing a neural network | Text Classification Tutorial Pt. 2 (Coding TensorFlow).
Prepare your data for ML | Text Classification Tutorial Pt. 1 (Coding TensorFlow).
Use TensorFlow to classify clothing images (Coding TensorFlow).
Build a neural network to perform classification | TensorFlow.js (Coding TensorFlow).
Prepare your dataset for machine learning (Coding TensorFlow).
Try TensorFlow.js in your browser (Coding TensorFlow).
TensorFlow Lite for iOS (Coding TensorFlow).
TensorFlow Lite for Android (Coding TensorFlow).
Introducing TensorFlow Lite (Coding TensorFlow).
All About TensorFlow Code (Coding TensorFlow).
Taught by
TensorFlow
